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H: Does running a Decision Tree classifier several times help?
To introduce, I am a novice in ML techniques. I recently had to write a scikit-learn based decision tree classifier to train on a real dataset. Someone suggested me that I must run mu model several thousand times and plot the accuracies on a graph. Here's ... |
H: Are Decision Trees Robust to Outliers
I read that decision trees (I am using scikit-learn's classifier) are robust to outlier. Does that mean that I will not have any side-effect if I choose not to remove my outliers?
AI: Yes.
Because decision trees divide items by lines, so it does not difference how far is a poin... |
H: Validation loss
I am having trouble wrapping my brain around validation loss. It's my understanding that loss is calculated at the end of the feed forward in a NeuralNet and is used in back propagation to update the weights. But I also see validation loss as a metric and don't understand fully what it is for other ... |
H: Why running the same code on the same data gives a different result every time?
I am using Keras in Jupyter Notebook.
I understood that for the same results, the random numbers should be produced from the same seed each time.
So, in the first of all my codes, I set random.seed as 1234 in a cell.
np.random.seed(1234... |
H: What database should I use?
I am a high-school students who is learning about data science in his free time. I have gotten a neural network to work which is able to solve xor problems. My neural network uses sigmoid as the activation function for both the hidden and output layers. It also has only one hidden layer.... |
H: Can I create pretrain model with tensorflow?
I takes a long time for train neural network model. It have to train every time when I run code. If I get high accuracy from training , Can I use same training model with another code without new training anymore ? How to do?
AI: You don't need to train your model each t... |
H: How to upload a saved file from google colab to a site such as kaggle or github?
We are able to load a file from a site such as kaggle and git hub to google collab, we apply the below code to download from other sites into google colab:
!wget nlp.stanford.edu/data/glove.6B.zip
but I am very curious to know if I ... |
H: Policy-based RL method - how do continuous actions look like?
I've read several times that Policy-based RL methods can work with continuous action space (move left 5 meters, move right 5.5312 meters), rather than with discrete actions, like Value-based methods (Q-learning)
If Policy-based methods produce probabilit... |
H: How to perform a reggression on 3 functions using a Neural Network
I am currently building a neural network using Keras to perform a regression.
I have 4 independent variables W,X,Y,Z. They are used to predict 3 different functions f1(W,X,Y,Z), f2(W,X,Y,Z), f3(W,X,Y,Z).
Should my output layer have 1 or 3 neurons? ... |
H: word2vec - log in the objective softmax function
I'm reading a TensorFlow tutorial on Word2Vec models and got confused with the objective function. The base softmax function is the following:
$P(w_t|h) = softmax(score(w_t, h) = \frac{exp[score(w_t, h)]}{\Sigma_v exp[score(w',h)]}$, where $score$ computes the compa... |
H: How to implement LSTM using Doc2Vec vectors?
I would like to build a ANN for text classification, which has an LSTM layer, and using weights obtained via a Doc2Vec model trained before:
model_doc2vec = Sequential()
model_doc2vec.add(Embedding(voacabulary_dim, 100, input_length=longest_document, weights=[training_we... |
H: Dataset with disproportionately more of a single label than any other
I'm using the data analysis software Orange to analyze rows of data with labels $\{H, T,L\}$. $T$ is the neutral state of the system I'm trying to model so data is almost always labeled with $T$. This leads to an extremely high $97$% classificat... |
H: Problem in Recommendation for categorical data?
I have been building a recommendation model to recommend certain questions in an interaction platform to users to help each other.
I have calculated an affinity score between categories to find which top categories are to be recommended. But each category has question... |
H: doc2vec - How does the inference step work in PV-DBOW
I am quite confused about how we generate new paragraph vectors in PV-DBOW?
If I want to use the embeddings to classify some text how would I generate a vector for a new paragraph?
In the original paper the authors wrote:
At prediction time, one needs to perfo... |
H: Early stopping and final Loss or weights of models
In a deep model, I used the Early stopping technique as below in Keras:
from keras.callbacks import EarlyStopping
early_stopping = [EarlyStopping(monitor='val_loss',
min_delta=0,
patience=2,
... |
H: when to use dot product and when to use the common product In neural networks?
I wanted to know when to use dot product and when to not , I also don't know when we must transpose an array and why should we , could someone help me to understand this ?
If you could give me the derivative of cost function with respect... |
H: Prepare data : many products per row
I would like to find how to change my data structure to make it compatible with a ML model, with the following constraints :
A Product is defined by {id, price, continuousVariable1, ..., continuousVariable10}
The training set is train.csv. Each line contains a date, a Produ... |
H: How do I predict continuous value from time series data?
I have a glove that have 2 IMUs (Inertial Measurement Unit) attached to it. It can give the rotation value as Quaternion (x,y,z,w) and acceleration of the hand (x,y,z).
I put it on my left hand and I want to predict the position of the hand relative to some f... |
H: RL agent, how to forbid actions?
In Q-learning, how to tell the agent that action $a_7$ is unavailable from within state $s_{t}$?
Is supplying a very large negative reward good, or might throw it off-track?
From what I read (link), it's best to work with small rewards (between -1.0 and 1.0)
AI: In Q-learning, how... |
H: Can we use a neural network to perform arithmetic operation between 2 numbers?
How to develop a neural network which can perform subtraction?
AI: It is an easy task. Make some training data, two inputs and one output. this is a regression task. You can train a simple MLP or you can employ RNNs such as LSTM for this... |
H: Anomaly detection on time series
I've just started working on an anomaly detection development in Python.
My data sets are a collection of timeseries. More in details, data are coming from some sensors/meters which record and collect data on boilers or other equipments.
As I said before, the data which I have to wo... |
H: Given data that is labeled as outliers, how can I classify data as outliers?
I have a dataset that is a mixture of sparse binary features and quantitative features. I only have definite outliers labeled. How should I approach trying to classify unlabeled data?
I considered using OSVM or other methods of one-class c... |
H: Efficient dimensionality reduction for large dataset
I have a dataset with ~1M rows and ~500K sparse features. I want to reduce the dimensionality to somewhere in the order of 1K-5K dense features.
sklearn.decomposition.PCA doesn't work on sparse data, and I've tried using sklearn.decomposition.TruncatedSVD but ge... |
H: Why does Bagging or Boosting algorithm give better accuracy than basic Algorithms in small datasets?
I was working with a small dataset, with 392 values, and it was kind of an imbalanced dataset, with 262 values belonging to class 1 and rest 130 to class 0. So I did the upsampling technique, importing sklearn.resam... |
H: Can Reinforcement learning be applied for time series forecasting?
Can Reinforcement learning be applied for time series forecasting?
AI: Yes, but in general it is not a good tool for the task, unless there is significant feedback between predictions and ongoing behaviour of the system.
To construct a reinforcemen... |
H: Image classification if rotated version same
I asked this question on stackoverflow but was advised to come here.
I have some images to classify. I see that Convolutional neural network may be best for this, e.g. here. However, for my images, their rotated versions (to any degree) is effectively same image. What s... |
H: MDP - RL, Multiple rewards for the same state possible?
This question is from An introduction to RL Pages 48 and 49. This question may also be related to below question, although I am not sure:
Cannot see what the "notation abuse" is, mentioned by author of book
On page 48, it is mentioned that p:S * R * S * A ->... |
H: Data Augmentation recommended pipeline
I want to perform image classification using Keras and a dataset made of 50 classes. At the moment, I have only 7 images per class and I need to perform data augmentation in order to train the model and obtain acceptable accuracy values.
I am using the ImageDataGenerator class... |
H: Python SkLearn Gradient Boost Classifier Sample_Weight Clarification
Using Python SkLearn Gradient Boost Classifier - is it true that sample_weight is modifying how the algorithm penalizes errors made on that particular class, rather than feeding more data into the trees by oversampling from that class. If you have... |
H: In natural language processing, why each feature requires an extra dimension?
I am reading Machine Learning by Example. I am trying to understand natural language processing. The book used Scikit-learn's fetch_20newsgroups data as an example.
The book mentioned that the text data in the 20 newsgroups dataset that w... |
H: Is the neural network in DQN used to learn like a supervised model?
Is the neural network in DQN used to learn like a supervised model?
AI: Is the neural network in DQN used to learn like a supervised model?
Yes.
In DQN, the neural network is used as a function approximator to learn the action value function $Q(... |
H: What should be 'y_train' in Keras LSTM?
I refer to the example given at the Keras website here:
from keras.models import Sequential
from keras.layers import LSTM, Dense
import numpy as np
data_dim = 16
timesteps = 8
num_classes = 10
# expected input data shape: (batch_size, timesteps, data_dim)
model = Sequential... |
H: RL Advantage function why A = Q-V instead of A=V-Q?
In RL Course by David Silver - Lecture 7: Policy Gradient Methods, David explains what an Advantage function is, and how it's the difference between Q(s,a) and the V(s)
Preliminary, from this post:
First recall that a policy $\pi$ is a mapping from each state, $... |
H: Complex HTMLs Data Extraction with Python
Does anybody know a way of extracting data with python from more convoluted website structures? For example, I'm trying to extract data from the players in the ATP profiles, but it's just so complicated I quit. I think they're pulling data from some database in the script a... |
H: Feature Extraction Using A CNN
I want to use a CNN to extract features from a dataset. My questions are:
What is the stopping criteria when training a CNN to extract features?
What is the difference between extracting features after training for 50 epochs or 100 epochs?
How should I choose the best layer for feat... |
H: A Neural Network That Learns Bitwise XOR
I am trying to build a deep neural network that learns the coordinate-coordinate bitwise XOR of two matrices, but it performs poorly.
For example, in the 2 bits case, its accuracy stays around 0.5. Here is the code snippet:
from keras.layers import Dense, Activation
from ke... |
H: Why does the naive bayes algorithm make the naive assumption that features are independent to each other?
Naive Bayes is called naive because it makes the naive assumption that features have zero correlation with each other. They are independent of each other. Why does naive Bayes want to make such an assumption?
A... |
H: Calculate whether datapoints are part of a larger distribution
I have some normally distributed variables (~800) and some variables that are in some way special (~30). I need to find out whether the special ones can be considered normal members of the distribution.
I drew a histogram of the full distribution with ... |
H: Imputation missing values other than using Mean, Median in python
I heard that Mean, Median isn't the best way to impute the missing values, why would that be?
In my scenario, I have data like this
Brand|Value
A|2,
A|NaN,
A|4,
B|8,
B|NaN,
B|10,
C|9,
C|11
if using mean imputation the data would be
Brand|Value
A|2,
... |
H: how to interpret predictions from model?
I'm working on a multi-classification problem - Recognizing flowers.
I trained the mode and I achieved accuracy of 0.99.
To predict, I did:
a = model.predict(train[:6])
output:
array([[5.12799371e-18, 2.08305119e-05, 1.14476855e-07, 1.28556788e-02,
1.46144101e-08, ... |
H: In batch normalization, shouldn't using DropConnect harm test accuracy?
In my understanding of batch normalization, mean and variance are calculated over the entire batch and then added to the population average. This average is then applied to the test set to estimate the mean and variance of the overall test set.... |
H: How to use scikit-learn normalize data to [-1, 1]?
I am using scikit-learn MinMaxScaler() to normalize to $[0, 1]$, but I want to normalize to $[-1, 1].$ What function do I have to use to normalize this way?
AI: Scaling between 0 and 1 is simply written for an array of values arr = $[x_{1}, x_{2}, ...., x_{n}]$ as ... |
H: What are some situations when normalizing input data to zero mean, unit variance is not appropriate or not beneficial?
I have seen normalization of input data to zero mean, unit variance many times in machine learning. Is this a good practice to be done all the time or are there times when it is not appropriate or ... |
H: How to choose dimensionality of the Dense layer in LSTM?
I have a task of multi-label text classification. My dataset has 1369 classes:
# data shape
print(X_train.shape)
print(X_test.shape)
print(Y_train.shape)
print(Y_test.shape)
(54629, 500)
(23413, 500)
(54629, 1369)
(23413, 1369)
For this task, I've decided to... |
H: How to know for sure if we can learn from a given data or not?
I want to know that given a set of data and a target, how we can know for sure whether we can learn from that data to make any inference or not?
AI: how can we know for sure
We can't.
A toy example to show why even humans can not do this for sure:
Ass... |
H: overfit a Random Forest
I am trying to overfit to the maximum a random forest classifier using scikit-learn to make some tests.
Does somebody know what hyperparameters I can tune to do that? Or does somebody know which other model I could apply to achieve a overfitted to the maximum a non-linear model?
AI: Decisio... |
H: How can generative models be used in machine learning classification applications?
My understanding of generative models is that they generate data to match certain statistical properties. Intuitively, I find it hard how generative models can be used for classification purposes. On the other hand, discriminative mo... |
H: NER: Extracting entities from an article
Description : I have dataset of categorised articles and to extract specific values from respective categorised article I have regex created for each category.
Aiming for:
Nlp techniques which learns the context of the content and avoids/minimizes the use of regex
If some n... |
H: Why Extra-trees should only be used within ensemble methods?
I was reading scikit-learn documentation for Extremely Randomized Trees and I found this warning:
Warning: Extra-trees should only be used within ensemble methods.
Why is that?
AI: In a random forest tree, a random subset of features is available for co... |
H: Reinforcement learning: decreasing loss without increasing reward
I'm trying to solve OpenAI Gym's LunarLander-v2.
I'm using the Deep Q-Learning algorithm. I have tried various hyperparameters, but I can't get a good score.
Generally the loss decreases over many episodes but the reward doesn't improve much.
How sho... |
H: What to do if training loss decreases but validation loss does not decrease?
I am training a LSTM model to do question answering, i.e. so given an explanation/context and a question, it is supposed to predict the correct answer out of 4 options.
My model architecture is as follows (if not relevant please ignore): ... |
H: Purpose of backpropagation in neural networks
I've just finished conceptually studying linear and logistic regression functions and their optimization as preparation for neural networks.
For example, say we are performing binary classification with logistic regression, let's define variables:
$x$ - vector containi... |
H: Extracting specific data from unstructured text - NER
I have a reasonably simple problem to solve. I need to extract reservations numbers from unstructured text. Based on my research, it seems to be an NER problem. Based on a visual analysis of the dataset, I could notice that the reservation number is frequently n... |
H: Meaning of dropout
What does model.add(Dropout(0.4)) mean in Keras?
Does it mean ignoring 40% of the neurons in the Neural Network? OR Does it mean ignoring the neurons that give probability = 0.4?
AI: It means that you randomly select 40% of the neurons and set their weights to zero for the forward and backward pa... |
H: Difference between isna() and isnull() in pandas
I have been using pandas for quite some time. But, I don't understand what's the difference between isna() and isnull(). And, more importantly, which one to use when identifying missing values in a dataframe.
What is the basic underlying difference of how a value is ... |
H: Plotting in PySpark?
I have been searching for methods to plot in PySpark.
I couldn't find any resource on plotting data residing in DataFrame in PySpark. The only methods which are listed are:
through method collect() which brings data into 'local' Python session and plot
through method toPandas() which converts... |
H: Sklearn SVM - how to get a list of the wrong predictions?
I am not an expert user. I know that I can obtain the confusion matrix, but I would like to obtain a list of the rows that have been classified in a wrong way in order to study them after classification.
On stackoverflow I found this Can I get a list of wron... |
H: Coding Problem - Extracting values from a column and forming a new dataframe [edited]
The problem statement requires extracting certain weather parameters for every hour in a particular date as denoted in the dataframe. The column 'hourly' consists of 24 lists in each entry, denoting weather parameters for each hou... |
H: Finding clusters in multidimensional data
I have a set of data from 3,000 records. There are 5 attributes per individual (labelled A - E). I can use Kendall's W (coefficient of concordance) to determine the concordance between any two records.
What I require is a way to discern any clusters which exist across the ... |
H: How to interpret a drastic accuracy loss while training a neuronal net (CNN)?
How can one interpret a drastic accuracy loss after ~38 epochs? Maybe more dropout should be added to the CNN network?
(x-axis shows the number of epochs)
AI: There could be several reasons:
Numeric stability issues + overfitting. Some... |
H: What is the difference between SGD classifier and the Logisitc regression?
To my understanding, the SGD classifier, and Logistic regression seems similar.
An SGD classifier with loss = 'log' implements Logistic regression and loss = 'hinge' implements Linear SVM. I also understand that logistic regression uses grad... |
H: What is the difference between multi-layer perceptron and generalized feed forward neural network?
I'm reading this paper:An artificial neural network model for rainfall forecasting in Bangkok, Thailand. The author created 6 models, 2 of which have the following architecture:
model B: Simple multilayer perceptron ... |
H: How to save and test CNN model on test set after training
My CNN model is trained on the training set and validated on the validation set, now I want to test it on test set, here is my code:
x_img = tf.placeholder(tf.float32, name='x_img')
y_label = tf.placeholder(tf.float32, name='y_label')
reshape = tf.reshape(x_... |
H: Navigating the jungle of choices for scalable ML deployment
I have prototyped a machine learning (ML) model on my local machine and would like to scale it to both train and serve on much larger datasets than could be feasible on a single machine. (The model was built with Python and Keras. It takes in a CSV table o... |
H: Can I treat text review analysis as a regression problem?
I am playing with a dataset that contains tripadvisor restaurant reviews and their labels (either 1, 2, 3, 4 or 5 stars).
Initially I was thinking of using it as a classification problem, applying softmax, cross-entropy and so on, however upon a second thou... |
H: What Does the Normalization Factor Mean in the AdaBoost Algorithm?
I am studying the AdaBoost algorithm. The update rule for a weak hypothesis is:
$Dt+1(i) = Dt(i)exp(−αtyiht(xi))/zt $
where $zt$ is a normalization factor chosen so that $Dt+1$ is a distribution.
What does the 'normalization factor' mean? Could I h... |
H: MinMaxScaler returned values greater than one
Basically I was looking for a normalization function part of sklearn, which is useful later for logistic regression.
Since I have negative values, I chose MinMaxScaler with: feature_range=(0, 1) as a parameter.
x = MinMaxScaler(feature_range=(0, 1)).fit_transform(x)
Th... |
H: How to compute unseen bi-grams in a corpus (for Good-Turing Smoothing)
Consider a (somewhat nonsensical) sentence - "I see saw a see saw"
The observed bi-grams would be:
"I see""see saw""saw a"and,"a see".
My aim is to smoothen out the probability mass of the bi-gram probabilities by using Good-Turing smoothing. F... |
H: Super basic logistic regression example
I am new to ML and I created a super basic logistic regression example with 4 points on the $x$ line that belong to two classes:
points = [[1, 1]]
points = points + [[2, 0]]
points = points + [[1.5, 1]]
points = points + [[2.5, 0]]
data = np.array([x[:-1] for x in points]... |
H: What is parts of speech technique in sentiment analysis?
In an article, I saw Sentiment Analysis using Parts Of Speech(POS) technique. When I searched I got some paper on POS but I couldn't understand what POS basically is. Though I am new to sentiment analysis please help me to understand POS.
AI: Parts of Speech ... |
H: Problem using Anaconda
I have installed Anaconda, but every time I open Terminal I have to go give the command:
export PATH=~/anaconda3/bin:$PATH
How can I fix this issue?
AI: You can make sure that command is executed for every terminal (meaning Anaconda will be found) by adding it to your user's bash profile.
... |
H: Replacing null with average in pyspark
I have a problem during upsampling operation in PySpark. My dataframe is:
df_upsampled.show()
+-------------------+------------------+
| et| average|
+-------------------+------------------+
|2018-08-15 00:10:00... |
H: What is the best way to visualize 10 Fold Cross Validation Scores?
I have trained a CNN model and I have applied 10 Fold Cross Validation because I don't have much data to train the classifier. Now I am unsure about how to visulize fold wise results. Please suggest some visualization charts or techniques to display... |
H: Using K-fold cross-validation in Keras on the data of my model
I would like to use K-fold cross-validation on my data of my model.
My codes in Keras is :
a = np.array(
[[283, 95, 72, 65],
[290, 100, 80, 72],
[120,170,130,122],
[100,230,110,200],
[300,100,200,500]]
)
X = a[:,0:2]
Y = a[:,3]
from sklearn.model_sel... |
H: Is there any consensus on choosing an appropriate ML approach?
I am studying data science at the moment and we are taught a dizzying variety of basic regression/classification techniques (linear, logistic, trees, splines, ANN, SVM, MARS, and so on....), along with a variety of extra tools (bootstrapping, boosting, ... |
H: How far can one go with excel?
in my business we handle all analytics through Excel. This includes mostly scheduling, production planning and accounting operations. We currently are looking into adding a bit of predictive modelling and Excel does suffice to a point, but doesn't have support for complex models.
As ... |
H: LOOKUP using 2 dataframes in Python
I have 2 dataframes:
df1
Id CategoryId
1 A
1 B
2 A
2 E
2 F
df2:
Id A B C D E F
1
2
I want to do a lookup which will help me fill up the values in df2 based on the values of df1
If df1 has id = 1 and CategoryId = A then I w... |
H: Minkowski distance with Missing Values
Im currently doing a subject for data science, and have the following point that im trying to understand.
We are looking to calculate distance in data sets where values may not be present. Now i know that R does this by default, but we are learning the "how" behind the what.
... |
H: Display Images (url) Inside Pandas Dataframe
I would like to display images (mostly jpg and png formats) directly from their url link inside a pandas dataframe. Imagine I already have the following dataframe:
id image_url
1 http://www.nstravel.ro/wp-content/uploads/2015/02/germany-profile_6023_600x450.jpg
2 https... |
H: How to correctly pass Word2Vec vectors as input to an LSTM
I am trying to build a text classifier using lstm which, in its first layer, has weights get by a Word2Vecmodel.
In order to build a matrix containing the indexes of each word for each sentence, I have tried: (as mentioned here)
X_tr_word2vec = np.array(X_t... |
H: Pandas vs Linux Datascience
I joined a data science learning community in my college and we are using linux terminal commands and awk commands to practice gathering some information from big datasets stored in csv files. About 7140596 columns by 29 rows in a single file.
A sample question would be: "What was the av... |
H: What is the difference between upsampling and bi-linear upsampling in a CNN?
I am trying to understand this paper and am unsure of what bi-linear upsampling is. Can anyone explain this at a high-level?
AI: In the context of image processing, upsampling is a technique for increasing the size of an image.
For exampl... |
H: Spatial Transformer Networks: how is theta differentiable?
In the paper Spatial Transformer Networks, the localization network's output, theta, is differentiable, given the current input feature map. How is this theta differentiable?
AI: In spatial transformer networks, basically, the concept of a localization netw... |
H: How to use build_analyzer in sklearn feature extraction
I'm trying to get list of n-gram tokens for text
Ex: 'How to use build_analyzer in sklearn feature extraction '
output :['How', 'use', 'build_analyzer', 'sklearn', 'feature', 'extraction', 'How use', 'use build_analyzer', 'build_analzer sklearn', 'sklearn fea... |
H: How to add numbers to the axes of a graph?
I am trying to make a graph of k (as in k-means) vs error, and I can't get it to show the actual number of k on the x-axis (1-15, not just the even numbers), nor any any numbers at all if I add a title to X.
I have looked at the data frame documentation and the matplotlib... |
H: data analysis EDA issues, indent or type
I am a newbie in DS world, right now i am working on some EDA practice, and run into an issue here.
Here is my code:
Convert some columns to numeric values
for column in cols:
auto[column] = pd.to_numeric(auto[column]
return auto
auto = read_auto_data()
error 1... |
H: Help with creating dimensions/features
It is quite hard to name the title properly as I just started to learn ML, will try to explain here. I want to practice ML by creating Movie suggestion algorithm. I came up with the following list of dimensions/features:
Rating
Number of votes
Genre
Actors
Directors
Writers
Y... |
H: Reinforcement learning: Discounting rewards in the REINFORCE algorithm
I am looking into the REINFORCE algorithm for reinforcement learning. I am having trouble understanding how rewards should be computed.
The algorithm from Sutton & Barto:
What does G, 'return from step t' mean here?
Return from step t to step ... |
H: What is new population in genetic algorithm?
Here is my (mis?)understanding of genetic algorithm:
Create n individuals. This is initial population
Calculate fitness of each individual in this population
for i in range(n):
select two individuals randomly with replacement from population with
probability o... |
H: What's the best metric for evaluate an estimator for a multi class problem with class imbalance dataset?
accuracy, precision, f1, ROC are good for binary single class problem.
but for more complex problem (imbalance multi-class problem), what should i use?
Do you have any recommendation?
AI: One standard metric is ... |
H: Appending DataFrames to lists in a dictionary - why does it seem like the list is being referenced by each new DataFrame?
I have a DataFrame that pairs one or more labels to a sample group and id, for a given sample stored in a database at SampleGroup/SampleID:
There are ~100 labels. I want to create binary models... |
H: Which is better for a beginner: R or Python?
From what I can tell, R and Python are the two most popular languages for data science.
My question is which one would you recommend for someone just starting out in data science? Does any one have any clear advantages on the other? Is any one easier to learn or does any... |
H: How to interpret my neural network with high accuracy but low probability in test results
I have built a classical ANN using keras which provides probability (using sigmoid function) of the outcomes (0 or 1). While the accuracy of the model is high when the model is fit ~90%, the outcome probability of the test set... |
H: What are the differences between logistic and linear regression?
I know that linear regression does "regression" and logistic regression does "classification". When we implement these two methods, the only difference I could notice is the loss function: linear regression uses a loss function like mean square error ... |
H: Binary text classification with TfidfVectorizer gives ValueError: setting an array element with a sequence
I am using pandas and scikti-learn to do binary text classification using text features encoded using TfidfVectorizer on a DataFrame. Here is some dummy code that illustrates what I'm doing:
import pandas as p... |
H: what is the one hot encoding for cancer data classification
I am working on a project to classify lung CT dataset using CNN and tensorflow, I know that the order for the category is cancer/no-cancer (only 2 classes), in more than one Github repository I see that they did one hot encoding like the code below:
if lab... |
H: Why is the logistic regression decision boundary linear in X?
The logistic regression model,
\begin{equation}
\operatorname{p}(X) = \frac{\operatorname{e}^{\beta_0 + \beta_1 X}}{1 + \operatorname{e}^{\beta_0 + \beta_1 X}}
\end{equation}
is said to create a decision boundary linear in $X$.
As far as I understand, on... |
H: Meaning of axes in a clustering plot
If you have n time series of rainfall measurements every hour (x=time, y=amount of rain), and compute the distance matrix between each pair of time series based on Dynamic Time Warping, and then plot the clusters, what do the X and Y axes on the cluster plot represent?
I have f... |
H: Why aren't Genetic Algorithms used for optimizing neural networks?
From my understanding, Genetic Algorithms are powerful tools for multi-objective optimization.
Furthermore, training Neural Networks (especially deep ones) is hard and has many issues (non-convex cost functions - local minima, vanishing and explodi... |
H: Optimizer for Convolutional neural network
What is the best optimizer for Convolutional neural network (CNN)?
Can I use RMSProp for CNN or only for RNN?
AI: Yes, you can use the same optimizers you are familiar with for CNNs.
I don't think that there is a best optimizer for CNNs. The most popular in my opinion is ... |
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